Fingerprints are the most widely used parameter for personal identification amongst all
biometrics based personal authentication systems. As most Automatic Fingerprint
Recognition Systems are based on local ridge features known as minutiae, marking
minutiae accurately and rejecting false ones is critically important. In this paper we propose
an algorithm for extracting minutiae from a fingerprint image using the binary Hit or Miss
transform (HMT) of mathematical morphology. We have developed and tested structuring
elements for different types of minutiae present in a fingerprint image to be used by the HMT
after preprocessing the image with morphological operators. This results in efficient minutiae
detection, thereby saving a lot of effort in the post processing stage. The algorithm is tested
on a large number of images. Experimental results depict the effectiveness of the proposed
technique.